{"id":"W2138556970","doi":"10.1109/icton.2007.4296232","title":"Cost-Effective Heuristics for Planning GMPLS Transport Networks with Conversion and Regeneration Capabilities","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Heuristics; Computer science; Scalability; Multiprotocol Label Switching; Computer network; Distributed computing; Network planning and design; Mathematical optimization; Quality of service; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001368197,0.001489798,0.001271567,0.0009875087,0.0007226277,0.001114628,0.001236724,0.001252119,0.002257728],"category_scores_gemma":[0.003680657,0.001146045,0.0006472798,0.001196227,0.0009852715,0.001235977,0.0009031907,0.0009776326,0.0002391641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001823093,"about_ca_system_score_gemma":0.002492156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01122891,"about_ca_topic_score_gemma":0.01505362,"domain_scores_codex":[0.9993359,0.000348171,0.00002988165,0.00008102366,0.00009338689,0.0001115677],"domain_scores_gemma":[0.9969311,0.002613852,0.0001588843,0.00006427285,0.000127013,0.0001048252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005405352,0.00004120419,0.0001772766,0.00005862488,0.00001817398,0.00004498664,0.00002581277,0.9845312,0.0001780367,0.004619802,0.0007968167,0.009454031],"study_design_scores_gemma":[0.00005220846,0.00002603647,0.00006523283,0.00001041838,0.000009837157,0.00001083382,0.00003639525,0.992215,0.0001949155,0.006886209,0.0004875113,0.000005474022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07108509,0.001361608,0.9154379,0.0008469747,0.0001166861,0.0005139719,0.0005731756,0.0007344082,0.009330206],"genre_scores_gemma":[0.4550684,0.0006009687,0.5406893,0.0001951239,0.00006193986,0.000615435,0.0006882834,0.0001360634,0.001944453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01122891,"threshold_uncertainty_score":0.02232713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01252982658532268,"score_gpt":0.238826692030936,"score_spread":0.2262968654456133,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}